Radiology & Imaging

Artificial intelligence (AI) models trained on large datasets are increasingly seen as the key to unlocking personalized treatments for brain disorders. An important bottleneck for scaling AI is the cost of data collection. This raises a fundamental dilemma: is it more cost-effective to scan more people for a short time, or fewer people for longer?

Two new open-source tools are set to make fluorescence lifetime imaging microscopy—or FLIM—faster, simpler and more accessible. Developed by Ph.D. student Sofia Kapsiani in Professor Gabi Kaminski Schierle’s Molecular Neuroscience Group, the tools tackle long-standing technical and practical barriers in biomedical imaging.

After a shoulder injury has been treated, patients are often left with a feeling of insecurity—many of them report that their shoulder “doesn’t hold” or “slips out easily.” When diagnosing shoulder instabilities, doctors often have to rely on these subjective assessments. The reason: Conventional imaging methods do not capture the movement of the shoulder.

As concern grows over racial bias in common medical tools like pulse oximeters, a new study shows that smartphones may offer a simple, accessible way to help correct the problem. Researchers at Brown University and Morgan State University have developed a method for using smartphone cameras to objectively measure skin tone, a factor known to affect the accuracy of pulse oximetry—the technique that monitors oxygen levels through the skin.

The Korea Research Institute of Standards and Science has developed a detachable acoustic lens that allows for easy adjustment of the focal length in ultrasonic inspection equipment. Much like swapping lenses on a DSLR camera to improve image quality, this technology enables users to optimize the resolution of ultrasonic imaging systems for specific inspection tasks. The innovation is expected to significantly enhance accuracy in both medical diagnostics and industrial safety inspections.

A first-of-its-kind generative AI system, developed in-house at Northwestern Medicine, is revolutionizing radiology—boosting productivity, identifying life-threatening conditions in milliseconds and offering a breakthrough solution to the global radiologist shortage, a large new study finds.

CT scans are a common test used by radiologists to examine what’s happening inside the body. These scans use a small amount of radiation, raising concerns that they could cause cancer.

When Dr. Shoshana Hallowell, a breast surgeon with McLaren Health System in Lapeer, Michigan, was diagnosed with breast cancer in 2020. She knew it put all of her first-degree relatives at higher risk of developing the same condition.

A study presented at ESCMID Global 2025 has demonstrated that an AI-powered lung ultrasound outperforms human experts by 9% in diagnosing pulmonary tuberculosis (TB).

Due to the inherent ambiguity in medical images like X-rays, radiologists often use words like “may” or “likely” when describing the presence of a certain pathology, such as pneumonia.